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Real-time video security system using chaos- improved advanced encryption standard (IAES)

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Abstract

Real-time multimedia applications are increasingly achieving success in the everyday world. Thereby, multimedia information relies on security to protect private life. The Advanced Encryption Standard (AES) has been designed to secure different applications. Yet, some limitations are given, making it inappropriate for secure video storation and transmission. The limitations are the time complexity, the multiple iterations, and the predefined substitution box. Thus, any user can use it to break the encryption. Moreover, the multiple iterations augment the need for CPU usage, and so the overall run time. Hence, it is necessary to modify the AES algorithm to make it more appropriate for securing video frames transmission over insecure channel. In this paper, an Improved AES (IAES) is put forward, which improves both diffusion and confusion in ciphered video. Our work consists in the following two main points: First, we propose to eliminate both shift-row and sub-byte transformations and replace them with a mix-row operation. This task reduces the run time, which presents a significant factor for real-time video transmission. Equally important, we propose to use the henon chaotic map in the key generation procedure, which provides more randomness. The Hash Algorithm SHA-3 is used to generate the initial conditions of the chaotic attractor. The video encryption procedure is verified with success, and the experimental results confirm that the novel algorithm combining chaos and IAES augments the entropy of the ciphered video by 15% and reduces the complexity time for both encryption and decryption compared to the standard one. Security analysis is successfully performed, and the results prove that our suggested technique provides the basics of cryptography with more correctness. The PRNG is tested by NIST 800–22 test suit, which indicates that it is suitable for secure image encryption. It provides a large key space of 2128 which resists the brute-force attack. All in all, the findings confirm that the novel security approach eliminates the limitation of the existing AES and provides a trade-off between speed and safety levels to secure video transmission.

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References

  1. Aabha N, Al A, Prasad PWC, Rasha A, Sami H (2020a) A novel modified chaotic simplified advanced encryption system (MCS-AES): mixed reality for a secure surgical tele-presence. Multimed Tools Appl. https://doi.org/10.1007/s11042-020-09478-1

  2. Aabha N, Al A, Prasad PWC, Rasha SA, Sami H (2020b) A novel modified chaotic simplified advanced encryption system (MCS-AES): mixed reality for a secure surgical tele-presence. Multimed Tools Appl. https://doi.org/10.1007/s11042-020-09478-1

  3. Agaian S, Raja R, Ravindranath Ch (2010) Logical Transform based encryption for multimedia systems. IEEE International Conference on Systems, Man and Cybernetics. https://doi.org/10.1109/ICSMC.2010.5642260.

  4. Alireza A, Mohammad J, Behnam G (2019a) An image encryption method based on chaos system and AES algorithm. J Supercomput 75:6663–6682. https://doi.org/10.1007/s11227-019-02878-7

    Article  Google Scholar 

  5. Alireza A, Mohammad JR, Behnam G (2019b) An image encryption method based on chaos system and AES algorithm. J Supercomput 75:6663–6682. https://doi.org/10.1007/s11227-019-02878-7

    Article  Google Scholar 

  6. Amal H, Anissa SM, Jihene M, Mohsen M (2020) An improved co-designed AES-ECC cryptosystem for secure data transmission. International Journal of Information and Computer Security (IJICS). https://doi.org/10.1504/IJICS.2020.108145

  7. Barakat ML, Mansingka AS, Radwan AG, Salama KN (2013) Generalized hardware post-processing technique for Chaos-based pseudorandom number generators. Electron Telecommun Res Inst 35(3):448–458. https://doi.org/10.4218/etrij.13.0112.0677

    Article  Google Scholar 

  8. Ben AA, Kadionik P, Masmoudi N, Levi H (2008) FPGA implementation of a HW/SW platform for multimedia embedded systems. Des Autom Embed Syst 12:293–311. https://doi.org/10.1007/s10617-008-9030-2

    Article  Google Scholar 

  9. Bentoutou Y, Bensikadour EL H, Talab N, Bounoua N (2019) An improved image encryption algorithm for satelite application. Advances in Space Research, Elsevier. 101016/jasr201909027

  10. Ganesan K, Singh I, Narain M (2008) Public key encryption of images and videos in real time using Chebyshev maps. In: Proceedings of the 2008 fifth international conference on computer graphics, imaging and visualization. IEEE Computer Society, Washington, DC, USA, pp 211–216. https://doi.org/10.1109/CGIV.2008.66

    Chapter  Google Scholar 

  11. Hassan El K, Wessam MS, Yasmine A (2019) New video encryption schemes based on chaotic maps. IET Image Process. https://doi.org/10.1049/iet-ipr.2018.5250

  12. Hayajneh T, Ullah S, Mohd BJ, Balagani KS (2017) An enhanced WLAN security system with FPGA. IEEE Syst J 11(4):2536–2545. https://doi.org/10.1109/JSYST.2015.2424702

    Article  Google Scholar 

  13. Hu Q, Mohammed G (2012) The accuracy of PSNR in predicting video quality for different video scenes and frame rates. Telecommun Syst 49:35–48. https://doi.org/10.1007/s11235-010-9351-x

    Article  Google Scholar 

  14. Hui X, Xiaojun T, Zhu W, Miao Z, Yang L, Jing M (2020) A robust video encryption for H.264 compressed bitstream based on cross-coupled chaotic cipher. Multimedia Systems 26:363–381. https://doi.org/10.1007/s00530-020-00648-7

    Article  Google Scholar 

  15. Jiang N, Dong X, Hu H et al (2019) Quantum image encryption based on Henon mapping. Int J Theor Phys 58:979–991. https://doi.org/10.1007/s10773-018-3989-7

  16. Jianming Z, Xi Z, Juan S, Xin Z, JIN W (2020a) A cascaded R-CNN with multiscale attention and imbalanced samples for traffic sign detection. IEEE Access. https://doi.org/10.1109/ACCESS.2020.2972338

  17. Jianming Zh, Lu C, Jin W, Yu X-G, Se-Jung L, Zafer AM, Amr T (2020b) Training Convolutional Neural Networks with Multi-Size Images and Triplet Loss for Remote Sensing Scene Classification. Sensors MDPI. https://doi.org/10.3390/s20041188.

  18. Kiah ML, Al-Bakri SH, Zaidan AA, Zaidan BB, Hussain M (2014a) Design and develop a video conferencing framework for real-time telemedicine applications using secure group-based communication architecture. J Med Syst 38(133):133–144. https://doi.org/10.1007/s10916-014-0133-y

    Article  Google Scholar 

  19. Kiah ML, Al-Bakri SH, Zaidan AA, Zaidan BB, Hussain M (2014b) Design and develop a video conferencing framework for real-time telemedicine applications using secure group-based communication architecture. J Med Syst 38(133):133–144. https://doi.org/10.1007/s10916-014-0133-y

    Article  Google Scholar 

  20. Li J, Chenyan W, Ch X, Zheng T, Hu G, Chin-Chen C (2018) A selective encryption scheme of CABAC based on video context in high efficiency video coding. Multimedia Tools Appl 77:12837–12851. https://doi.org/10.1007/s11042-017-4916-2

    Article  Google Scholar 

  21. Li Y, Jiaohua Q, Xi X, Yun T, Li Q, Lingyun X (2020) Coverless real-time image information hiding based on image block matching and dense convolutional network. J Real-Time Image Proc. https://doi.org/10.1007/s11554-019-00917-3

  22. Lin D, Xu W, Yuantao C (2020) Density peaks clustering by zero-pointed samples of regional group borders. Hindawi Computational Intelligence and Neuroscience. https://doi.org/10.1155/2020/8891778

  23. Luoyu Z, Tao Z, Yumeng T, Huang H (2020) Fraction-order total variation image blind restoration based on self-similarity features. IEEE Access. https://doi.org/10.1109/ACCESS.2020.2972269

  24. Nattional Institute of Standards and Technology (NIST) (2001) Advanced Encryption standard (AES), Federal Information Processing Standards Publications (FIPS PUBS) 197–26

  25. Nios II integrated development environment. http://www.altera.com/products/ip/processors/nios2/ni2-index.html

  26. Qingqing H, Liejun W, Yongming L, Qi J (2020) Video encryption scheme using hybrid encryption technology. International Journal of Internet Protocol Technology. https://doi.org/10.1504/IJIPT.2020.105046

  27. Seyed Sh M, Yucheng C, Chunming T (2019) A new algorithm for medical color images encryption using chaotic systems. Entropy 21:577. https://doi.org/10.3390/e21060577

    Article  MathSciNet  Google Scholar 

  28. Shannon C (1949) Communication theory of secrecy systems. Bell Syst Tech J. https://doi.org/10.1002/j.1538-7305.1949.tb00928.x

  29. Shuli C, Liejun W, Naixiang A, Qingqing H (2020) A selective video encryption scheme based on coding characteristics. Symmetry 2020(12):332. https://doi.org/10.3390/sym12030332

    Article  Google Scholar 

  30. Sonia K, Medien Z, Adel B, Taoufik S, Yousef D, Rached T (2015) FPGA-based real-time implementation of AES algorithm for video encryption. Recent Advances in Telecommunications, Informatics and Educational Technologies. ISBN: 978-1-61804-262-0

  31. Th e μClinux project http://www.uClinux.org

  32. Tzouveli P, Ntalianis K, Kollias S (2004) Security of human video objects by incorporating a chaos-based feedback cryptographic scheme. ACM Multimedia. https://doi.org/10.1145/1027527.1027609

  33. Wickramage C, Sahama T, Fidge C (2016) Anatomy of log files: implications for information accountability measures. e-Health Netw Appl Serv (Healthcom):1–6. https://doi.org/10.1109/HealthCom.2016.7749426

  34. Xingyan W, Yuanyun Z, Huili Z, Kang G (2016) A novel color image encryption using alternate chaotic mapping structure. Opt Lasers Eng 82:79–86. https://doi.org/10.1016/j.optlaseng.2015.12.006

    Article  Google Scholar 

  35. Fei Yu , Li Li ,Binyong He ,Yuanyuan H, Changqiong Shi, Shuo Cai ,Yun S ,Sichun Du ,and Qiuzhen W (2019) Analysis and FPGA Realization of a Novel 5D Hyperchaotic Four-Wing Memristive System, Active Control Synchronization ,and Secure Communication Application. Hindawi. https://doi.org/10.1155/2019/4047957.

  36. Yua F, Liua L, Xiao L, Kenli L, Shuo C (2019) A robust and fixed-time zeroing neural dynamics for computing time-variant nonlinear equation using a novel nonlinear activation function. Neurocomputing. https://doi.org/10.1016/j.neucom.2019.03.053

  37. Yuantao C, Weihong X, Jingwen KY (2018a) The fire recognition algorithm using dynamic feature fusion and IVSVM classifier. Clust Comput 22:S7665–S7675. https://doi.org/10.1007/s10586-018-2368-8(0123456789().,-volV)(0123456789().,-volV)

    Article  Google Scholar 

  38. Yuantao C, Jie X, Weihong X, Jingwen Z (2018b) A novel online incremental and decremental learning algorithm based on variable support vector machine. Clust Comput. https://doi.org/10.1007/s10586-018-1772-4

  39. Yuantao C, Jin W, Xi C, Arun KS, Kai Y, Ca Z (2019a) Image super-resolution algorithm based on dual-channel convolutional neural networks. MDPI Appl Sci 9:2316. https://doi.org/10.3390/app9112316

    Article  Google Scholar 

  40. Yuantao C, Jin W, Xi C, Mingwei Z (2019b) Single-image super-resolution algorithm based on structural self-similarity and deformation block features. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2911892

  41. Yuantao C, Jin W, Runlong X, Qian Z, Ca Z (2019c) The visual object tracking algorithm research based on adaptive combination kernel. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-018-01171-4

  42. Yuantao C, Jin W, Songjie L, Xi C, Xi J, Xi J (2019d) Multiscale fast correlation filtering tracking algorithm based on feature fusion model. Wiley Concurrency Computat Pract Exper. https://doi.org/10.1002/cpe.5533

  43. Yuantao C, Jiajun T, Qian Z, Kai Y, Xi C, Xi J, Xi R (2020a) Saliency detection via the improved hierarchical principal component analysis method. Hindawi Wireless Communications and Mobile Computing Volume. https://doi.org/10.1155/2020/8822777

  44. Yuantao C, Jiajun T, Linwu L, Jie X, Runlong X, Jingbo X, Qian Z, Kai Y (2020b) Research of improving semantic image segmentation based on a feature fusion model. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-02066-z

  45. Yuantao C, Li L, Jiajun T, Xi R, Qian Z, Kai Y, Xi J, Xi C (2020c) The improved image inpainting algorithm via encoder and similarity constraint. Vis Comput. https://doi.org/10.1007/s00371-020-01932-3

  46. Yue W, Noonan JP, Agaian S (2011) NPCR and UACI randomness tests for image encryption. Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT):31–38

  47. Zhang X, Chen W (2008) A new chaotic algorithm for image encryption. Int Conf Audio Language Image Process 4(3):889–892. https://doi.org/10.1109/ICALIP.2008.4590187

    Article  Google Scholar 

  48. Zheng Y, Jin J (2015) A novel image encryption scheme based on Hénon map and compound spatiotemporal chaos. Multimed Tools Appl 74:7803–7820. https://doi.org/10.1007/s11042-014-2024-0

  49. Zhou W, Alan CB, Hamid SR, Si EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4)

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Authors and Affiliations

  1. Electronics and Micro-Electronics Laboratory, University of Monastir, Monastir, Tunisia

    Amal Hafsa, Marwa Fradi, Anissa Sghaier, Jihene Malek & Mohsen Machhout

  2. Department of Electronics, Sousse University, Higher Institute of Applied Sciences and Technology, LR99ES30 E_E Lab, Sousse, Tunisia

    Jihene Malek

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  1. Amal Hafsa
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Hafsa, A., Fradi, M., Sghaier, A. et al. Real-time video security system using chaos- improved advanced encryption standard (IAES). Multimed Tools Appl 81, 2275–2298 (2022). https://doi.org/10.1007/s11042-021-11668-4

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